蓝色 发表于 2018-10-19 08:08 
老师,感谢您的回复~关于面板数据交互和分组的系数差异问题,想请教您一下,希望老师指点~谢谢老师~
对于下面这个例子, 第一个回归中(交互项) tenure 的系数,和第二第三个回归中(分组)tenure的系数存在差异~
(例子是 help xtreg 中example的数据)
webuse nlswork,clear
xtset idcode
. xtreg ln_w age c.tenure##union , fe r
Fixed-effects (within) regression Number of obs = 19,010
Group variable: idcode Number of groups = 4,134
R-sq: Obs per group:
within = 0.1276 min = 1
between = 0.1534 avg = 4.6
overall = 0.1301 max = 12
F(4,4133) = 290.67
corr(u_i, Xb) = 0.1272 Prob > F = 0.0000
(Std. Err. adjusted for 4,134 clusters in idcode)
--------------------------------------------------------------------------------
| Robust
ln_wage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
---------------+----------------------------------------------------------------
age | .0096922 .0008612 11.25 0.000 .0080038 .0113806
tenure | .0196865 .0012793 15.39 0.000 .0171783 .0221946
1.union | .1271028 .0118425 10.73 0.000 .1038851 .1503206
union#c.tenure |
1 | -.007151 .0015312 -4.67 0.000 -.0101529 -.0041491
_cons | 1.353125 .0243775 55.51 0.000 1.305332 1.400918
---------------+----------------------------------------------------------------
sigma_u | .405353
sigma_e | .25627106
rho | .71443966 (fraction of variance due to u_i)
--------------------------------------------------------------------------------
. xtreg ln_w age tenure if union==0, fe r
Fixed-effects (within) regression Number of obs = 14,539
Group variable: idcode Number of groups = 3,744
R-sq: Obs per group:
within = 0.1118 min = 1
between = 0.0933 avg = 3.9
overall = 0.0930 max = 12
F(2,3743) = 370.32
corr(u_i, Xb) = 0.0900 Prob > F = 0.0000
(Std. Err. adjusted for 3,744 clusters in idcode)
------------------------------------------------------------------------------
| Robust
ln_wage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
age | .0092085 .0009338 9.86 0.000 .0073777 .0110393
tenure | .0190461 .0013294 14.33 0.000 .0164396 .0216526
_cons | 1.346987 .0266217 50.60 0.000 1.294793 1.399182
-------------+----------------------------------------------------------------
sigma_u | .41488747
sigma_e | .25338348
rho | .72833798 (fraction of variance due to u_i)
------------------------------------------------------------------------------
. xtreg ln_w age tenure if union==1, fe r
Fixed-effects (within) regression Number of obs = 4,471
Group variable: idcode Number of groups = 1,625
R-sq: Obs per group:
within = 0.1347 min = 1
between = 0.0634 avg = 2.8
overall = 0.0845 max = 12
F(2,1624) = 135.19
corr(u_i, Xb) = 0.0484 Prob > F = 0.0000
(Std. Err. adjusted for 1,625 clusters in idcode)
------------------------------------------------------------------------------
| Robust
ln_wage | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
age | .014007 .0025921 5.40 0.000 .0089227 .0190913
tenure | .0081815 .0028126 2.91 0.004 .0026647 .0136982
_cons | 1.442803 .0697704 20.68 0.000 1.305953 1.579652
-------------+----------------------------------------------------------------
sigma_u | .39602032
sigma_e | .21951085
rho | .76497076 (fraction of variance due to u_i)
------------------------------------------------------------------------------